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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study
Published 2025-08-01“…Purpose: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. …”
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Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage
Published 2025-06-01“…Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. …”
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Research on unmanned mining truck path planning based on grey wolf optimization adaptive hybrid A* and artificial potential field
Published 2025-06-01“…Experimental results demonstrate that, compared to the standard HA* algorithms and the improved hybrid A* (IHA*) algorithms, GWO-HAPF improves computational efficiency in global planning by an average of 80% and 14.9%, respectively, reduces path length by over 9.8%, and increases smoothness by over 53%. …”
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1744
Verifiable secure image retrieval for cloud-assisted IoT environments
Published 2025-03-01“…The proposed scheme improves image retrieval accuracy and security while optimizing computational and storage resources, making it suitable for cloud-assisted IoT environments.…”
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1745
Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks
Published 2025-06-01“…While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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Addressing power quality challenges in hybrid renewable energy systems through STATCOM devices and advanced gray wolf optimization technique
Published 2025-03-01“…This algorithm acts to improve control parameters, thus increasing the system's reliability. …”
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1747
Volumetric Patch-Based Super-Resolution Reconstruction of Hyperpolarized <sup>13</sup>C Cardiac MRI
Published 2024-01-01“…The reconstruction accuracy was asymptotically improved as the patch size increased whereas intra-segmental spatial fluctuations were preserved better with smaller patches. …”
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1748
Biomimetic Computing for Efficient Spoken Language Identification
Published 2025-05-01“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith...
Published 2025-03-01“…Furthermore, advancements in transfer learning and data augmentation have improved artificial intelligence adoption in regions with limited datasets. …”
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Optimized radiofrequency shimming using low-heating B1+-mapping in the presence of deep brain stimulation implants: Proof of concept.
Published 2024-01-01“…The present work addresses this issue in proof of concept using electromagnetic simulations and experimental PTX MRI. A two-step optimization algorithm is proposed and examined for a cylindrical phantom with an implanted wire to enable 1) robust B1+ mapping with low localized heating; and 2) robust RF shimming PTX with low localized heating and good B1+ homogeneity over a large imaging volume. …”
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1751
Daily reference evapotranspiration prediction in Iran: A machine learning approach with ERA5-land data
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1752
Distributed Robust Low-Carbon Economic Dispatch of Power Systems Considering Extreme Scenarios
Published 2025-04-01“…[Results] Case studies on an improved IEEE 39-node system using the column-and-constraint generation (C&CG) algorithm demonstrate that, compared with traditional deterministic and DRO models based on typical scenarios, the proposed approach increases scheduling costs by 7.11% and 14.37% respectively, but reduces renewable curtailment rates by 8.28% and 34.65%, and load shedding rates by 8.19% and 33.32%. …”
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Optimizing Geospatial Data for ML/CV Applications: A Python-Based Approach to Streamlining Map Processing by Removing Irrelevant Areas
Published 2024-12-01“…The research results of the paper reveal substantial file size reduction, and improved processing efficiency, thus making the optimized geospatial graphical data more practical for ML/CV applications, while still maintaining the original data quality and relevance of the analyzed parcels or infrastructure.…”
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1754
Seismic Optimization of Fluid Viscous Dampers in Cable-Stayed Bridges: A Case Study Using Surrogate Models and NSGA-II
Published 2025-04-01“…Results demonstrate that the ANN-based approach effectively addresses multi-objective optimization challenges while providing a robust framework for improved seismic performance in cable-stayed bridges. …”
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1755
A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN
Published 2025-01-01“…To deal with those challenges, we advocate a novel routing framework that is both steady and power-efficient, leveraging an Improved Type-2 Fuzzy Logic System (IT2FLS) optimized by means of the Reptile Search Algorithm (RSA). …”
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Innovative Business Models Towards Sustainable Energy Development: Assessing Benefits, Risks, and Optimal Approaches of Blockchain Exploitation in the Energy Transition
Published 2025-08-01“…Blockchain has the potential to change energy services towards this direction. To optimally exploit blockchain, innovative business models need to be designed, identifying the opportunities emerging from unmet needs, while also considering potential risks so as to take action to overcome them. …”
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An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations
Published 2024-11-01“…In conclusion, by incorporating nighttime light remote sensing data along with advanced machine learning techniques, this study markedly improves forecasting accuracy for waste production while offering effective optimization strategies for site selection and recovery route planning—thereby establishing a robust data foundation aimed at refining urban solid waste management systems.…”
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Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response
Published 2025-04-01“…This study proposes a two-stage distributionally robust optimization (DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES. …”
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